prometheus/tsdb/tsdbutil/chunks.go
beorn7 630bcb494b storage: Use separate sample types for histogram vs. float
Previously, we had one “polymorphous” `sample` type in the `storage`
package. This commit breaks it up into `fSample`, `hSample`, and
`fhSample`, each still implementing the `tsdbutil.Sample` interface.

This reduces allocations in `sampleRing.Add` but inflicts the penalty
of the interface wrapper, which makes things worse in total.

This commit therefore just demonstrates the step taken. The next
commit will tackle the interface overhead problem.

Signed-off-by: beorn7 <beorn@grafana.com>
2023-04-13 19:25:24 +02:00

148 lines
3.5 KiB
Go

// Copyright 2018 The Prometheus Authors
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
package tsdbutil
import (
"fmt"
"github.com/prometheus/prometheus/model/histogram"
"github.com/prometheus/prometheus/tsdb/chunkenc"
"github.com/prometheus/prometheus/tsdb/chunks"
)
type Samples interface {
Get(i int) Sample
Len() int
}
type Sample interface {
T() int64
V() float64 // TODO(beorn7): Rename to F().
H() *histogram.Histogram
FH() *histogram.FloatHistogram
Type() chunkenc.ValueType
}
type SampleSlice []Sample
func (s SampleSlice) Get(i int) Sample { return s[i] }
func (s SampleSlice) Len() int { return len(s) }
// ChunkFromSamples requires all samples to have the same type.
func ChunkFromSamples(s []Sample) chunks.Meta {
return ChunkFromSamplesGeneric(SampleSlice(s))
}
// ChunkFromSamplesGeneric requires all samples to have the same type.
func ChunkFromSamplesGeneric(s Samples) chunks.Meta {
mint, maxt := int64(0), int64(0)
if s.Len() > 0 {
mint, maxt = s.Get(0).T(), s.Get(s.Len()-1).T()
}
if s.Len() == 0 {
return chunks.Meta{
Chunk: chunkenc.NewXORChunk(),
}
}
sampleType := s.Get(0).Type()
c, err := chunkenc.NewEmptyChunk(sampleType.ChunkEncoding())
if err != nil {
panic(err) // TODO(codesome): dont panic.
}
ca, _ := c.Appender()
for i := 0; i < s.Len(); i++ {
switch sampleType {
case chunkenc.ValFloat:
ca.Append(s.Get(i).T(), s.Get(i).V())
case chunkenc.ValHistogram:
ca.AppendHistogram(s.Get(i).T(), s.Get(i).H())
case chunkenc.ValFloatHistogram:
ca.AppendFloatHistogram(s.Get(i).T(), s.Get(i).FH())
default:
panic(fmt.Sprintf("unknown sample type %s", sampleType.String()))
}
}
return chunks.Meta{
MinTime: mint,
MaxTime: maxt,
Chunk: c,
}
}
type sample struct {
t int64
v float64
h *histogram.Histogram
fh *histogram.FloatHistogram
}
func (s sample) T() int64 {
return s.t
}
func (s sample) V() float64 {
return s.v
}
func (s sample) H() *histogram.Histogram {
return s.h
}
func (s sample) FH() *histogram.FloatHistogram {
return s.fh
}
func (s sample) Type() chunkenc.ValueType {
switch {
case s.h != nil:
return chunkenc.ValHistogram
case s.fh != nil:
return chunkenc.ValFloatHistogram
default:
return chunkenc.ValFloat
}
}
// PopulatedChunk creates a chunk populated with samples every second starting at minTime
func PopulatedChunk(numSamples int, minTime int64) chunks.Meta {
samples := make([]Sample, numSamples)
for i := 0; i < numSamples; i++ {
samples[i] = sample{t: minTime + int64(i*1000), v: 1.0}
}
return ChunkFromSamples(samples)
}
// GenerateSamples starting at start and counting up numSamples.
func GenerateSamples(start, numSamples int) []Sample {
return generateSamples(start, numSamples, func(i int) Sample {
return sample{
t: int64(i),
v: float64(i),
}
})
}
func generateSamples(start, numSamples int, gen func(int) Sample) []Sample {
samples := make([]Sample, 0, numSamples)
for i := start; i < start+numSamples; i++ {
samples = append(samples, gen(i))
}
return samples
}